The ideas of local search and random walks have been used successfully in several recent satisficing planners. Random Walk-Driven Local Search (RW-LS) is a strong new addition to this family of planning algorithms. The method uses a greedy best-first search driven by a combination of random walks and direct node evaluation. In this way, RW-LS balances between exploration and exploitation. The a...

Standard single-objective methods such as value iteration are not applicable to multi-objective Markov decision processes (MOMDPs) because they depend on a maximization, which is not defined if the rewards are multi-dimensional. As a result, special multi-objective algorithms are needed to find a set of policies that contains all optimal trade-offs between objectives, i.e. a set of Pareto optim...

Physician workforce planning tools are needed to address the adequacy of the nation’s physician workforce to meet its health needs. Since health care is an inherently local phenomenon, physician supply and demand need to be understood in the local area context. Therefore, we seek to build a Local Area Physician Workforce Planning Model that emphasizes a local perspective. To that end, we are de...

We introduce a novel proximity query, called connection collision query (CCQ), and use it for efficient and exact local planning in sampling-based motion planners. Given two collision-free configurations, CCQ checks whether these configurations can be connected by a given continuous path that either lies completely in the free space or penetrates any obstacle by at most ε , a given threshold. O...

Planning problems can be solved with a large variety of different approaches, and a significant amount of work has been devoted to the automation of planning processes using different kinds of methods. This paper focuses on the use of specific local search algorithms for real-world production planning based on experiments with real-world data, and presents an adapted local search guided by evol...

In this article we introduce a neural eld approach for local path planning of an autonomous mobile robot. The robot's heading direction is determined by the localized peak and its velocity by the maximum activation in the eld. We emphasize the neural eld's ability to keep the path planning stable even in the case of noisy sensor data or varying environments. The theoretical framework is validat...

We address trajectory generation for the snakeboard, a system commonly studied in the geometric mechanics community. Our approach derives a solution using body coordinates and local trajectory information, leading to a more intuitive solution compared to prior work. The simple forms of the solution clearly show how they depend on local curvature and desired velocity profile, allowing for a desc...

open local energy requirements, the need for regional energy planning in the process of macro-planning can make significant energy. in this respect, the outer part of the direct effects of energy production and consumption locally effective, less energy planning processes will be huge. in this paper, the issue of continuity of energy supply, long-term access to resources and lower emissions fro...

Successful operation of micro aerial vehicles in partially known environments requires globally consistent plans based on incomplete environment models and quick reactions to unknown obstacles by means of real-time planning of collision-free trajectories. In this paper, we propose a complete layered mission and navigation planning system based on coarse prior knowledge and local maps from omnid...